At first sight, an image of deep space and a slide of cancer cells may not appear to have much in common. However by using technology used to identify distant galaxies to spot rogue cancer cells, a team of scientists in the U.K. have managed to bridge that gap.

Scientists at the charity Cancer Research UK teamed up with researchers from the Institute of Astronomy in 2010 in an unlikely collaboration that could radically improve the diagnosis and treatment of cancer.

The first results of that collaboration were published in the British Journal of Cancer on Wednesday. Researchers were able to adapt techniques used by astronomers for picking up faint objects of interest out of dense images of the night-sky to pick out differences in stained tumor samples.

Raza Ali, the lead author of the study from Cancer Research, said in a statement: “We’ve exploited the natural overlap between the techniques astronomers use to analyze deep sky imaged from the largest telescopes and the need to pinpoint subtle differences in the staining of tumor samples down the microscope.”

Cancer Research say that spotting these differences is key to the understanding of why some cancers progress faster than others, as well as of why patients respond differently to treatments.

Up until now, the traditional means of picking out the differences in the staining of tumor samples required the trained eye of a pathologist looking down a microscope. This new automated system could dramatically speed up that process, analyzing up to 4,000 individual images a day.

To test the accuracy of the software , the team looked at the tumor samples of some 2,000 breast cancer patients.

“The results have been even better than we’d hoped, with our new automated approach performing with accuracy comparable to the time-consuming task of scoring images manually, after only relatively minor adjustments to the formula,” says Ali.

The team plans on expanding to a larger international study involving samples from over 20,000 breast cancer patients to test the accuracy of their original findings.

While the process of automation could be a big breakthrough, the charity argues that machines are nevertheless still not as accurate as the human eye in identifying crucial differences in tumor samples.

To deal with that backlog of data, Cancer Research launched in October last year what it claims to be the world’s first citizen science project called Cell Slider. The project has a website where anyone can go to score and classify actual tumor samples, freeing up scientists to analyze the terabytes of data produced by labs much faster.

Thus far the site has enabled them to sift through in three months 18 months worth of tumor samples. So while the stargazing method may not prove fruitful in the end, it seems that the charity have a useful crowd sourced option to fall back on.